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Hyeongjun Yang

ACL 2026×2对齐与偏好检索与知识可解释性效率与系统强化学习与后训练
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一作贡献30
核心/参与12
方向广度10
合作网络6
1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #2/5ACL 2026Poster· Natural Language Processing

LLM s as Knowledge Graph Refiners: Mitigating Factual Inconsistencies in Generative Knowledge Extraction

Donghyun Kim · Hyeongjun Yang · Seokju Hwang · Kyong-Ho Lee · Chanhee Lee

摘要

Knowledge graphs (KGs) provide a structured representation of real-world facts as triples consisting of entities and their relationships. With the rapid progress of large language models (LLMs), recent studies increasingly explore LLMs for end-to-end KG construction from text. In particular, gene...

检索与知识对齐与偏好可解释性OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

Data-Efficient Adaptation to Contextual Shifts in LLM -based Conversational Recommendation

Hyeongjun Yang · Donghyun Kim · Seokju Hwang · Midan Shim · KyuHwan Yeom · KaeHyun Um · Kyong-Ho Lee

摘要

Large language model (LLM)-based conversational recommender systems (CRSs) have demonstrated strong capabilities in capturing user preferences and generating contextually relevant recommendations. Nevertheless, the recommendation quality of the models frozen after training inevitably degrades und...

对齐与偏好效率与系统强化学习与后训练OpenReview 项目页

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